AI Tooling SDE: Agentic GenAI at Scale

Amazon Web Services (AWS)

New York (NY)

On-site

USD 158,000 - 214,000

Full time

5 days ago
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Job summary

Amazon Web Services (AWS) is seeking a Software Development Engineer to join the Specialist AI Tooling engineering team within STT, building AI-native, agentic solutions that transform how AWS technical specialists and field teams develop expertise, get matched to customer engagements, and how AWS service teams consume customer feedback at scale.

If you want to build production agentic AI systems that impact thousands of users daily – not research prototypes, but real AI agents solving real

Qualifications

  • 3 years of non-internship professional software development experience.
  • 2 years of non-internship design or architecture experience of new and existing systems.
  • 1 year of software development engineer or related occupational experience.
  • 1 year of designing and developing large-scale distributed software applications using languages like C#, C, Java, or Perl.

Responsibilities

  • Design and implement production agentic AI systems using LLMs, knowledge graphs, RAG, and multi-agent orchestration.
  • Build and optimize GenAI-powered pipelines including summarization, content ranking, skill assessment, and intelligent routing.
  • Develop prompt engineering strategies, evaluation frameworks, and guardrails for production LLM systems.
  • Implement embedding and retrieval strategies for a knowledge base.
  • Design and build scalable distributed systems and APIs powering the TFC Hub platform.

Skills

Software development
System design
Multi-threaded programming
Programming language proficiency

Education

Bachelor's degree in computer science or equivalent

Job description

Amazon Web Services (AWS) is seeking a Software Development Engineer to join the Specialist AI Tooling engineering team within STT, building AI-native, agentic solutions that transform how AWS technical specialists and field teams develop expertise, get matched to customer engagements, and how AWS service teams consume customer feedback at scale.

If you want to build production agentic AI systems that impact thousands of users daily – not research prototypes, but real AI agents solving real

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